Energy-Efficient Data Gathering Using Sleep Scheduling and Spatial Correlation Based on Data Distribution in Wireless Sensor Networks

In this paper, we extend an energy-efficient data gathering method, named ODAS/SS, to improve the accuracy of monitoring applications in wireless sensor networks. ODAS/SS adopts spatial interpolation and sleep scheduling mechanisms in order to suppress the energy consumption and the variation in residual energy among nodes. In the original ODAS/SS, nodes which keep awake are selected only based on geographical locations and residual energies. On the other hand, our extended method determines whether each node keeps awake or not according to not only the locations and residual energies of nodes but also data distribution in the target region. Furthermore, we present the results of simulation experiments to verify the effectiveness of the extended method.